Riak doesn't use consistent hashing

Jonathan Langevin jlangevin at loomlearning.com
Thu May 26 09:57:47 EDT 2011


That sounds quite disconcerting. What happens to the performance of the
cluster when this occurs?*

<http://www.loomlearning.com/>
Jonathan Langevin
Systems Administrator
Loom Inc.
Wilmington, NC: (910) 241-0433 - jlangevin at loomlearning.com -
www.loomlearning.com - Skype: intel352
*


On Thu, May 26, 2011 at 1:54 AM, Greg Nelson <grourk at dropcam.com> wrote:

>  I've been doing some digging through the details of how a node joins a
> cluster.  When you hear that Riak uses consistent hashing, you'd expect it
> to distribute keys to nodes by hashing keys onto the ring AND hashing nodes
> onto the ring.  Keys belong to the closest node on the ring, in the
> clockwise direction.  Add a node, it hashes onto the ring and takes over
> some keys.  Ordinarily the node would hash onto the ring in several places,
> to achieve better spread.  Some data (roughly 1 / #nodes) moves to the new
> node from each of the other nodes, and everything else stays the same.
>
> In what Amazon describes as operationally simpler (strategy 3 in the Dynamo
> paper), the ring is instead divided into equally-sized partitions.  Nodes
> are hashed onto the ring, and preflists are calculated by walking clockwise
> from a partition, skipping partitions on already visited nodes.  Riak does
> something similar: it divides the ring into equally-sized partitions, then
> nodes "randomly" claim partitions.  However, the skipping bit isn't part of
> Riak's preflist calculation.  Instead, nodes claim partitions in such a way
> as to be spaced out by target_n_val, to obviate the need for skipping.
>
> Now, getting back to what happens when a node joins.  The new node
> calculates a new ring state that maintains the target_n_val invariant, as
> well as trying to keep even spread of partitions per node.  The algorithm
> (default_choose_claim) is heuristic and greedy in nature, and recursively
> transfers partitions to the new node until optimal spread is achieved,
> maintaining target_n_val along the way.  But if -- during one of those
> recursive calls -- it can't meet the target_n_val, it will throw up its
> hands and completely re-do the whole ring (by calling claim_rebalance_n).
>  Striping the partitions across nodes, in a round-robin fashion.  When that
> happens, most of the data needs to be handed off between nodes.
>
> This happens a lot, with many ring sizes.  With ring_creation_size=128
> (i.e., 128 partitions), it will happen when adding node 9 (87.5% of data
> moves), adding node 12 (82%), adding node 15 (80%), adding node 19 (94%).
>  It happens with all ring sizes >= 128 (256, 512, 1024, ...).  It appears
> that any ring_creation_size (64 by default) is safe for growing to 8 nodes
> or so.  But if you want to go beyond that...  A ring size of >= 128 with
> more than 8 nodes doesn't seem all that unusual, surely someone has hit this
> before?  I've filed a bug report here:
> https://issues.basho.com/show_bug.cgi?id=1111
>
> Anyway, this feels like a bit of a departure from consistent hashing.  In
> fact, could this not be replaced by normal hashing + a lookup table mapping
> intervals of the hash space to nodes?  And isn't that simply sharding?
>
> At any rate, I believe the claim algorithm can be improved to avoid those
> "throw up hands and stripe everything" scenarios.  In fact, here is such an
> implementation:  https://github.com/basho/riak_core/pull/55.  It is still
> heuristic and greedy, but it seems to do a better job of avoiding re-stripe.
>  Test results are attached in a zip on the bug linked above.  I'd love to
> get the riak_core gurus at Basho to look at this and help validate it.  It
> probably could use some cleaning up, but I want to make sure there aren't
> other invariants or considerations I'm leaving out -- besides maintaining
> target_n_val, keeping optimal partition spread, and minimizing handoff
> between ring states.
>
> -Greg
>
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>
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